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Impact of MiFID II on the Market Volatility—Analysis on Some Developed and Emerging European Stock Markets

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  • Marius Cristian Miloș

    (Faculty of Economics and Business Administration, West University of Timisoara, 300115 Timisoara, Romania)

Abstract

The paper investigates whether the implementation of MiFID II, a packet of financial legislation applying broadly to European Union financial markets, has led to a change in the volatility of some European developed and emerging stock markets. We show that for the developed capital markets considered in the analysis, MiFID II did not lead to a decrease in the volatility of capital markets. On the contrary, for all analysis intervals considered (3 months, 6 months, 12 months, 18 months and 24 months), the impact on volatility is positive, with volatility increasing in the case of the FTSE 100, CAC40 and DAX stock indexes. There is a similar significant relationship for the Czech stock market, but only over the three-month interval. For the Polish and Romanian stock markets, which enforced MiFID II later, a negative impact of MiFID II on volatility could also be observed. In the Romanian market, MiFID II had a negative impact on volatility on the short-term horizon, while for the Polish market, the impact of MiFID II on volatility is noticeable on a longer term of 24 months.

Suggested Citation

  • Marius Cristian Miloș, 2021. "Impact of MiFID II on the Market Volatility—Analysis on Some Developed and Emerging European Stock Markets," Laws, MDPI, vol. 10(3), pages 1-11, June.
    • Handle: RePEc:gam:jlawss:v:10:y:2021:i:3:p:55-:d:585793
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    References listed on IDEAS

    as
    1. Anselmi, Giulio & Petrella, Giovanni, 2021. "Regulation and stock market quality: The impact of MiFID II provision on research unbundling," International Review of Financial Analysis, Elsevier, vol. 76(C).
    2. Madhavan, Ananth, 1996. "Security Prices and Market Transparency," Journal of Financial Intermediation, Elsevier, vol. 5(3), pages 255-283, July.
    3. Pastor, Lubos & Stambaugh, Robert F., 2003. "Liquidity Risk and Expected Stock Returns," Journal of Political Economy, University of Chicago Press, vol. 111(3), pages 642-685, June.
    4. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2002. "Order imbalance, liquidity, and market returns," Journal of Financial Economics, Elsevier, vol. 65(1), pages 111-130, July.
    5. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    6. Brogaard, Jonathan & Garriott, Corey, 2019. "High-Frequency Trading Competition," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(4), pages 1469-1497, August.
    7. Darrat, Ali F. & Rahman, Shafiqur & Zhong, Maosen, 2003. "Intraday trading volume and return volatility of the DJIA stocks: A note," Journal of Banking & Finance, Elsevier, vol. 27(10), pages 2035-2043, October.
    8. Aghanya, Daniel & Agarwal, Vineet & Poshakwale, Sunil, 2020. "Market in Financial Instruments Directive (MiFID), stock price informativeness and liquidity," Journal of Banking & Finance, Elsevier, vol. 113(C).
    9. Jen-Sin Lee & Kuan-Ling Lai & Yu-Ko Huang, 2015. "Information transparency and idiosyncratic risk," Applied Economics Letters, Taylor & Francis Journals, vol. 22(12), pages 934-937, August.
    10. Copeland, Thomas E, 1976. "A Model of Asset Trading under the Assumption of Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 31(4), pages 1149-1168, September.
    11. Ariadna Dumitrescu, 2010. "Liquidity and Optimal Market Transparency," European Financial Management, European Financial Management Association, vol. 16(4), pages 599-623, September.
    12. Tim Bollerslev & Julia Litvinova & George Tauchen, 2006. "Leverage and Volatility Feedback Effects in High-Frequency Data," Journal of Financial Econometrics, Oxford University Press, vol. 4(3), pages 353-384.
    13. Hibbert, Ann Marie & Daigler, Robert T. & Dupoyet, Brice, 2008. "A behavioral explanation for the negative asymmetric return-volatility relation," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2254-2266, October.
    14. Jennings, Robert H & Starks, Laura T & Fellingham, John C, 1981. "An Equilibrium Model of Asset Trading with Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 36(1), pages 143-161, March.
    15. Lamdin, Douglas J., 2001. "Implementing and interpreting event studies of regulatory changes," Journal of Economics and Business, Elsevier, vol. 53(2-3), pages 171-183.
    16. Thomas C. Chiang & Zhuo Qiao & Wing-Keung Wong, 2010. "New evidence on the relation between return volatility and trading volume," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(5), pages 502-515.
    17. Madhavan, Ananth & Porter, David & Weaver, Daniel, 2005. "Should securities markets be transparent?," Journal of Financial Markets, Elsevier, vol. 8(3), pages 265-287, August.
    18. Ekkehart Boehmer & Gideon Saar & Lei Yu, 2005. "Lifting the Veil: An Analysis of Pre‐trade Transparency at the NYSE," Journal of Finance, American Finance Association, vol. 60(2), pages 783-815, April.
    19. Terrence Hendershott & Charles M. Jones & Albert J. Menkveld, 2011. "Does Algorithmic Trading Improve Liquidity?," Journal of Finance, American Finance Association, vol. 66(1), pages 1-33, February.
    20. Bloomfield, Robert & O'Hara, Maureen, 1999. "Market Transparency: Who Wins and Who Loses?," The Review of Financial Studies, Society for Financial Studies, vol. 12(1), pages 5-35.
    21. Hagströmer, Björn & Nordén, Lars, 2013. "The diversity of high-frequency traders," Journal of Financial Markets, Elsevier, vol. 16(4), pages 741-770.
    22. Hassan & Eliza Wu, 2015. "Sovereign credit ratings, growth volatility and the global financial crisis," Applied Economics, Taylor & Francis Journals, vol. 47(54), pages 5825-5840, November.
    23. Charles Corrado & Cameron Truong, 2007. "Forecasting Stock Index Volatility: Comparing Implied Volatility And The Intraday High–Low Price Range," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 30(2), pages 201-215, June.
    24. Bingxu Fang & Ole-Kristian Hope & Zhongwei Huang & Rucsandra Moldovan, 2020. "The effects of MiFID II on sell-side analysts, buy-side analysts, and firms," Review of Accounting Studies, Springer, vol. 25(3), pages 855-902, September.
    25. Harris, Lawrence, 1987. "Transaction Data Tests of the Mixture of Distributions Hypothesis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(2), pages 127-141, June.
    26. Andersen, Torben G, 1996. "Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility," Journal of Finance, American Finance Association, vol. 51(1), pages 169-204, March.
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